The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-volume work covering all major areas of the application of logic to artificial intelligence and logic programming. The authors are chosen on an international basis and are leaders in the fields covered. Volume 5 is the last in this well-regarded series. Logic is now widely recognized as one of the foundational disciplines of computing. It has found applications in virtually all aspects of the subject, from software and hardware engineering to programming languages and artificial intelligence. In response to the growing need for an in-depth survey of these applications the Handbook of Logic in Artificial Intelligence and its companion, the Handbook of Logic in Computer Science have been created. The Handbooks are a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying themes in the various areas. Some mathematical background is assumed, and much of the material will be of interest to logicians and mathematicians. Volume 5 focuses particularly on logic programming. The chapters, which in many cases are of monograph length and scope, emphasize possible unifying themes.

The handbook of logic in artificial intelligence and logic programming is an international reference work in five volumes. It has been created in response to the growing need for an in-depth survey of the applications of logic in artifical intelligence. The dramatic increase in research in recent years means that logic is now widely recognised as one of the foundational disciplines of computing and has found applications in virtually all aspects of the subject, from software engineeringand hardware to programming languages and artificial intelligence. Yet this handbook is the first authoritative text to pull together the accumulated research level material, and as such is a unique and invaluable reference source. The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-author multi-volume work covering all the major areas of application of logic to artifical intelligence and logic programming. The Handbook comprises five volumes, each an in-depth overview of one of the major topics in this area. It is the result of years of co-operative effort by internationally renowned researchers in the field, and will no doubt be the standard reference work in artifical intelligence and logic programming for years to come- essential reading for all those interested in this subject. This latest volume covers, among other subjects, epistemic reasoning, time and change for AI, and temporal nonmonotonic reasoning.

BL A comprehensive five volume work BL Sets the standard in reference for logic and artificial intelligence The Handbook of Logic in Artificial Intelligence and Logic Programming will be published in five volumes. The handbook comes in response to the growing need for an in-depth survey of the applications of logic in artificial intelligence and computer science. This first volume presents the logical foundations and deduction methodologies extensively used in AI.

BL A comprehensive five volume work BL Sets the standard in reference for logic and artificial intelligence The Handbook of Logic in Artificial Intelligence and Logic Programming will be published in five volumes. The handbook comes in response to the growing need for an in-depth survey of the applications of logic in artificial intelligence and computer science. This first volume presents the logical foundations and deduction methodologies extensively used in AI.

BL A comprehensive five volume work BL Sets the standard in reference for logic and artificial intelligence The Handbook of Logic in Artificial Intelligence and Logic Programming will be published in five volumes. The handbook comes in response to the growing need for an in-depth survey of the applications of logic in artificial intelligence and computer science. This first volume presents the logical foundations and deduction methodologies extensively used in AI.

The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-author volume work covering all major areas of application of logic to AI and logic programming. Initially there will be six volumes containing a total of 43 articles, each article averaging around 75 pages in length but with some rather longer as the subject may demand. The authors are chosen on an international basis and are leaders in the fields covered. The Handbook is a closely co-ordinated work which has been under development for the past five years. Volume 3 covers nonmonotonic reasoning.

Highly parallel machines have been available for many years but, because advances in hardware have always outpaced progress in software development, designers and users of these machines have yet to realize their full potential. Until recently there have been few, if any, high-class parallel programming languages that could be implemented on the wide variety of parallel processing systems in use. This book helps to redress the balance by teaching programming techniques as well as performance analysis of parallel programming languages and architectures using logic programming; specifically, it focuses on the Prolog-like languages OR-parallel Prolog and AND-parallel FGHC. Parallel Logic Programmingbrings to light practical applications of a previously esoteric/theoretical area of parallel logic programming and is unique in presenting programming hand-in-hand with performance analysis of real empirical measurements. Its quantitative approach to symbolic parallel programming provides students and professionals with tools for implementing and critically evaluating larger projects. The book includes useful chapter summaries, programming projects, and a glossary.

Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to recent techniques for learning relational concepts. In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance. Inductive Logic Programming includes a definition of the basic ILP problem and its variations (incremental, with queries, for multiple predicates and predicate invention capabilities), a description of bottom-up operators and techniques (such as least general generalization, inverse resolution, and inverse implication), an analysis of top-down methods (mainly MIS and FOIL-like systems), and a survey of methods and languages for specifying inductive bias. Logic Programming series